Machine Learning Market To Hit 44.1% CAGR to 2022: North America Held Largest Market Share During Forecast Period

The machine learning market size is expected to grow from $1.41 Billion in 2017 to $8.81 Billion by 2022, at a CAGR of 44.1% driven by Technological advancement and proliferation in data generation.

APAC is estimated to grow at the highest CAGR during the forecast period. Factors, such as continual growth in the mobile network, increasing the complexity of business, rise in demand for intelligent business processes, and exponential growth in data generation throughout the industry verticals are driving the machine learning market in the APAC region.

Browse 71 Market Data Tables and 56 Figures spread through 160 Pages and in-depth TOC on "Machine Learning Market by Vertical (BFSI, Healthcare and Life Sciences, Retail, Telecommunication, Government and Defense, Manufacturing, Energy and Utilities), Deployment Mode, Service, Organization Size, and Region - Global Forecast to 2022"

The North American region is expected to have the largest market share during the forecast period. The major growth drivers for this region are the large-scale investments in implementing machine learning services due to the growth in demand for processed data. Moreover, recently the region also witnessed the widespread adoption of cloud-based machine learning platform among large enterprises and SMEs across multiple verticals.

Target Audience For This Study:
Machine learning/Artificial Intelligence (AI) solution and service providers
System integrators
Enterprise data center professionals
End-users/consumers/enterprise users
Telecommunication providers
Mobile network operators
Cloud service providers
Data center software vendors
IoT device/wearable device manufacturers
Cognitive and Artificial Intelligence (AI) technology experts/providers
Analytics service providers
Managed service providers
Training and education service providers

The major issue in front of most of the organizations while incorporating machine learning in their business process is the lack of skilled employees including analytical talent, and the demand for those who can monitor analytical content is even greater.

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Professional service segment is expected to have a larger market share during the forecast period. The service segment in the machine learning market includes professional and managed services. Majority of the companies do not have the expertise to successfully manage infrastructure, and hence, they outsource these services to third-party partners to maintain the level of security and safety. The growth of the professional services segment is mainly governed by the complexity of operations and increasing deployment of machine learning solutions.

Large enterprises segment is expected to have a larger market size during the forecast period. The organization size segment in the machine learning market includes Small and Medium-Sized Enterprises (SMEs) and large enterprises. Emergence in the demand for cloud computing, cloud storage, IoT connected devices, and excessive use of smart phones are some of the prime reasons why large enterprises have turned toward machine learning for processing data. In large enterprises, machine learning has a huge potential for the big data technology in allowing precise decision-making for superior performance.

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In the process of determining and verifying the market size for several segments and subsegments gathered through secondary research, extensive primary interviews were conducted with the key people.

By Company Type - Tier 1 - 18%, Tier 2 - 48%, and Tier 3 - 34%
By Designation – C-level -22%, Director-level -43%, and Others-35%
By Region –North America -42%, EMEA (Europe, Middle East and Africa) -32%, and APAC (AsiaPacific)- 26%

The major machine learning vendors are Microsoft Corporation (Washington, US), IBM Corporation (New York, US), SAP SE (Wall dorf, Germany), SAS Institute Inc. (North Carolina, US), Google, Inc. (California, US), Amazon Web Services Inc. (Washington, US), Baidu, Inc. (Beijing, China), Big ML, Inc. (Oregon, US), Fair Isaac Corporation (FICO) (California, US), Hewlett Packard Enterprise Development LP (HPE) (California, US), Intel Corporation (California, US), AG (Zurich, Switzerland), RapidMiner, Inc. (Massachusetts, US), Angoss Software Corporation (Toronto, Canada), (California, US), Alpine Data (California, US), Domino Data Lab, Inc. (California, US), Dataiku (Paris, France), Luminoso Technologies, Inc. (Massachusetts, US), Trademark Vision (Pennsylvania, US), Fractal Analytics Inc. (New Jersey, US), TIBCO Software Inc. (California, US), Teradata (Ohio, US), Dell Inc. (Texas, US), and Oracle Corporation (California, US).

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Research Coverage

The machine learning market has been segmented on the basis of verticals, deployment modes, organization sizes, services, and region. The machine learning is segmented on the basis of verticals into Banking, Financial Services, and Insurance (BFSI), energy and utilities, healthcare and life sciences, retail, telecommunication, manufacturing, government and defense, and others (transportation, agriculture, media and entertainment, and education). The verticals are further segmented on the basis of application areas, applications of machine learning in BFSI includes fraud and risk management, investment prediction, sales and marketing campaign management, customer segmentation, digital assistance, and others (compliance management and credit underwriting).

Applications of machine learning in healthcare and life sciences includes disease identification and diagnosis, image analytics, drug discovery/manufacturing, personalized treatment, and others (clinical trial research and epidemic outbreak prediction). Applications of machine learning in retail includes inventory planning, up sell and cross channel marketing, segmentation and targeting, recommendation engines, and others (customer ROI and lifetime value and customization management). Applications of machine learning in telecommunication includes customer analytics, network optimization, network security, and others (digital assistance/contact centers analytics and marketing campaign analytics).

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Applications of machine learning in government and defense includes threat intelligence, autonomous defense system, and others (sustainability and operational analytics). Applications of machine learning in manufacturing includes predictive maintenance, demand forecasting, revenue estimation, supply chain management, and others (root cause analysis and telematics). Applications of machine learning in energy and utilities includes power/energy usage analytics, seismic data processing, smart grid management, carbon emission, and others (customer specific pricing and renewable energy management).

The services offered in the machine learning market include professional and managed services. The deployment modes in the machine learning market include the cloud and on-premises. The organization sizes are segmented into Small and Medium-Sized Enterprises (SMEs) and large enterprises. Finally, on the basis of regions, the machine learning market is segmented into North America, Europe, APAC, Middle East and Africa (MEA), and Latin America.

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Release ID: 240406